The long-term effect of the Earned Income Tax Credit on women's physical and mental health

Potential mechanisms linking poverty alleviation and health: an analysis of benefit spending among recipients of the U.S. earned income tax credit

BACKGROUND

The earned income tax credit (EITC) is the largest U.S. poverty alleviation program for low-income families, disbursed annually as a lump-sum tax refund. Despite its well-documented health impacts, the mechanisms through which the EITC affects health are not well understood. The objective of this analysis was to examine self-reported spending patterns of tax refunds among EITC recipients to clarify potential pathways through which income may affect health.

METHODS

We first examined spending patterns among 2020-2021 Assessing California Communities' Experiences with Safety Net Supports (ACCESS) study participants (N = 241) and then stratified the analysis by key demographic subgroups.

RESULTS

More than half of EITC recipients reported spending their tax refunds on bills and debt (52.3%), followed by 49.4% on housing, and 37.8% on vehicles. Only 3.3% reported spending on healthcare. (Note: respondents could list more than one possible spending category.) Participants ages 30 + were more likely to spend on bills and debt relative to those ages 18-29 (57.6% versus 39.4%, respectively). Other subgroup analyses did not yield significant findings.

CONCLUSIONS

Our findings suggest that EITC recipients primarily use their refunds on bills and debt, as well as on household and vehicle expenses. This supports the idea of the EITC as a safety net policy which addresses key social determinants of health.

Unconditional cash transfers and mental health symptoms among parents with low incomes: Evidence from the 2021 child tax credit

The COVID-19 pandemic increased anxiety and depression in the U.S. population, particularly among low-income households, parents, and Black and Hispanic adults. To address the negative impacts of the pandemic, Congress temporarily expanded the Child Tax Credit (CTC) in 2021, providing a near-universal, unconditional cash transfer to families with children. Using a quasi-experimental, parameterized difference-in-differences research design, we examine the effects of the 2021 monthly CTC on symptoms of anxiety and depression in a large, national sample of parents with low incomes (N∼15,000). We study potential differences in the associations by race/ethnicity and consider whether CTC effects were stronger after a longer treatment period (for instance, due to greater dosage or delayed effects). We find some evidence that the monthly credit reduced parental anxiety and depression symptoms, although the results were not robust throughout all model specifications. Analyses stratified by race/ethnicity show stronger associations for non-Hispanic Black parents than for non-Hispanic White parents or Hispanic parents, although differences were small. We also find the credit reduced anxiety (but not depression) symptoms after three months of payments, suggesting that it took some time for the CTC to affect mental health symptoms. Overall, this study suggests that recurring cash transfers to families in poverty in the U.S. may have small beneficial effects on parental mental health.

The English Teaching Methods in the Field of Public Health in Colleges and Universities Based on Artificial Intelligence Technology

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities to continuously optimize the English teaching system. This technology can help colleges and universities to carry out English education in the field of public health and can improve the overall quality of English teaching in colleges and universities. Artificial intelligence technology is related to the optimization of English teaching environment in colleges and universities. At the same time, artificial intelligence technology also affects the development of society and the future of the country. Artificial intelligence technology provides more accurate data resources for English teaching in the field of public health in colleges and universities. It also provides rich and reliable educational technology means for teachers. This technology improves the scientific nature of English education in the field of public health in colleges and universities. This paper comprehensively uses a variety of methods such as case empirical analysis and qualitative analysis to analyze the application mode of artificial intelligence technology in English teaching. This paper closely integrates artificial intelligence technology with English education in the field of public health in colleges and universities. College English teaching methods, teachers' personal factors, and teacher-student relationship will all have an impact on students' health. This paper makes a comprehensive analysis of the theoretical basis and actual situation of English teaching in colleges and universities, and then constructs an innovative system of English education in the field of public health in colleges and universities. Based on this, the text adopts a structured analysis method to conduct an in-depth analysis of the application mode of artificial intelligence technology. This paper analyzes in detail the opportunities and challenges faced by the development of public health education in colleges and universities. At the same time, this paper also summarizes the objective laws of the development of public health education, and then comprehensively analyzes the impact of artificial intelligence technology on the English education model in colleges and universities.